Monday, February 06. 2017

Note: following the two previous posts about algorythms and bots ("how do they ... ?), here comes a third one.

Slighty different and not really dedicated to bots per se, but which could be considered as related to "machinic intelligence" nonetheless. This time it concerns techniques and algoritms developed to understand the brain (BRAIN initiative, or in Europe the competing Blue Brain Project).

In a funny reversal, scientists applied techniques and algorythms developed to track human intelligence patterns based on data sets to the computer itself. How do a simple chip "compute information"? And the results are surprising: the computer doesn't understand how the computer "thinks" (or rather works in this case)!

This to confirm that the brain is certainly not a computer (made out of flesh)...

When you apply tools used to analyze the human brain to a computer chip that plays Donkey Kong, can they reveal how the hardware works?

Many research schemes, such as the U.S. government’s BRAIN initiative, are seeking to build huge and detailed data sets that describe how cells and neural circuits are assembled. The hope is that using algorithms to analyze the data will help scientists understand how the brain works.

But those kind of data sets don’t yet exist. So Eric Jonas of the University of California, Berkeley, and Konrad Kording from the Rehabilitation Institute of Chicago and Northwestern University wondered if they could use their analytical software to work out how a simpler system worked.

They settled on the iconic MOS 6502 microchip, which was found inside the Apple I, the Commodore 64, and the Atari Video Game System. Unlike the brain, this slab of silicon is built by humans and fully understood, down to the last transistor.

The researchers wanted to see how accurately their software could describe its activity. Their idea: have the chip run different games—including Donkey Kong, Space Invaders, and Pitfall, which have already been mastered by some AIs—and capture the behavior of every single transistor as it did so (creating about 1.5 GB per second of data in the process). Then they would turn their analytical tools loose on the data to see if they could explain how the microchip actually works.

For instance, they used algorithms that could probe the structure of the chip—essentially the electronic equivalent of a connectome of the brain—to establish the function of each area. While the analysis could determine that different transistors played different roles, the researchers write in PLOS Computational Biology, the results “still cannot get anywhere near an understanding of the way the processor really works.”

Elsewhere, Jonas and Kording removed a transistor from the microchip to find out what happened to the game it was running—analogous to so-called lesion studies where behavior is compared before and after the removal of part of the brain. While the removal of some transistors stopped the game from running, the analysis was unable to explain why that was the case.

In these and other analyses, the approaches provided interesting results—but not enough detail to confidently describe how the microchip worked. “While some of the results give interesting hints as to what might be going on,” explains Jonas, “the gulf between what constitutes ‘real understanding’ of the processor and what we can discover with these techniques was surprising.”

It’s worth noting that chips and brains are rather different: synapses work differently from logic gates, for instance, and the brain doesn’t distinguish between software and hardware like a computer. Still, the results do, according to the researchers, highlight some considerations for establishing brain understanding from huge, detailed data sets.

First, simply amassing a handful of high-quality data sets of the brains may not be enough for us to make sense of neural processes. Second, without many detailed data sets to analyze just yet, neuroscientists ought to remain aware that their tools may provide results that don’t fully describe the brain’s function.

As for the question of whether neuroscience can explain how an Atari works? At the moment, not really.

Thursday, June 23. 2016

Note: we've been working recently at fabric | ch on a project that we couldn't publish or talk about for contractual reasons... It concerned a relatively large information pavilion we had to create for three new museums in Switzerland (in Lausanne) and a renewed public space (railway station square). This pavilion was supposed to last for a decade, or a bit longer. The process was challenging, the work was good (we believed), but it finally didn't get build...

Sounds sad but common isn't it?

...

We'll see where these many "..." will lead us, but in the meantime and as a matter of documentation, let's stick to the interesting part and publish a first report about this project.

It consisted in an evolution of a prior spatial installation entitled Heterochrony (pdf). A second post will follow soon with the developments of this competition proposal. Both posts will show how we try to combine small size experiments (exhibitions) with more permanent ones (architecture) in our work. It also marks as well our desire at fabric | ch to confront more regularly our ideas and researches with architectural programs.

On the jury paper was written, under "price" -- as we didn't get paid for the 1st price itself -- : "Réalisation" (realization).

Just below in the same letter, "according to point 1.5 of the competition", no realization will be attributed... How ironic! We did work further on an extended study though.

A few words about the project taken from its presentation:

" (...) This platform with physically moving parts could almost be considered an archaeological footbridge or an unknown scientific device, reconfigurable and shiftable, overlooking and giving to see some past industrial remains, allowing to document the present, making foresee the future.

The pavilion, or rather pavilions, equipped with numerous sensor systems, could equally be considered an "architecture of documentation" and interaction, in the sense that there will be extensive data collected to inform in an open and fluid manner over the continuous changes on the sites of construction and tranformations. Taken from the various "points of interets' on the platform, these data will feed back applications ("architectural intelligence"?), media objects, spatial and lighting behaviors. The ensemble will play with the idea of a combination of various time frames and will combine the existing, the imagined and the evanescent. (...) "

Funilly, we've picked a very similar name for a very similar data service we've set up for ourselves and our friends last year, during an exhibition at H3K: Datadroppers (!), with a different set of references in our mind (Drop City? --from which we borrowed the colors-- "Turn on, tune in, drop out"?) Even if our service is logically much more grassroots, less developed but therfore quite light to use as well.

We developed this project around data dropping/picking with another architectural project in mind that I'll speak about in the coming days: Public Platform of Future-Past. It was clearly and closely linked.

"Universal" is back in the loop as a keyword therefore... (I would rather adopt a different word for myself and the work we are doing though: "Diversal" --which is a word I'm using for 2 yearnow and naively thought I "invented", but not...)

"The Wolfram Data Drop is an open service that makes it easy to accumulate data of any kind, from anywhere—setting it up for immediate computation, visualization, analysis, querying, or other operations." - which looks more oriented towards data analysis than use in third party designs and projects.

"Datadroppers is a public and open data commune, it is a tool dedicated to data collection and sharing that tries to remain as simple, minimal and easy to use as possible." Direct and light data tool for designers, belonging to designers (fabric | ch) that use it for their own projects...

Tuesday, June 07. 2016

Note: I've posted several articles about automation recently. This was the occasion to continue collect some thoughts about the topic (automation then) so as the larger social implications that this might trigger.

But it was also a "collection" that took place at a special moment in Switzerland when we had to vote about the "Revenu the Base Inconditionnel" (Unconditional Basic Income). I mentioned it in a previous post ("On Algorithmic Communism"), in particular the relation that is often made between this idea (Basic Income / Universal Income) and the probable evolution of work in the decades to come (less work for "humans" vs. more for "robots").

Well, the campain and votation triggered very interesting debates among the civil population, but in the end and predictably, the idea was largely rejected (~25% of the voters accepted it, with some small geographical areas that indeed acceted it at more than 50% --urban areas mainly--. Some where not so far, for exemple the city capital, Bern, voted at 40% for the RBI).

This was very new and a probably too (?) early question for the Swiss population, but it will undoubtedlybecome a growing debate in the decades to come. A question that has many important associated stakes.

More generally, thinking the Future in different terms than liberalism is an absolute necessity. Especially in a context where, also as stated, "Automation and unemployment are the future, regardless of any human intervention".

IN THE NEXT FEW DECADES, your job is likely to be automated out of existence. If things keep going at this pace, it will be great news for capitalism. You’ll join the floating global surplus population, used as a threat and cudgel against those “lucky” enough to still be working in one of the few increasingly low-paying roles requiring human input. Existing racial and geographical disparities in standards of living will intensify as high-skill, high-wage, low-control jobs become more rarified and centralized, while the global financial class shrinks and consolidates its power. National borders will continue to be used to control the flow of populations and place migrant workers outside of the law. The environment will continue to be the object of vicious extraction and the dumping ground for the negative externalities of capitalist modes of production.

It doesn’t have to be this way, though. While neoliberal capitalism has been remarkably successful at laying claim to the future, it used to belong to the left — to the party of utopia. Nick Srnicek and Alex Williams’s Inventing the Future argues that the contemporary left must revive its historically central mission of imaginative engagement with futurity. It must refuse the all-too-easy trap of dismissing visions of technological and social progress as neoliberal fantasies. It must seize the contemporary moment of increasing technological sophistication to demand a post-scarcity future where people are no longer obliged to be workers; where production and distribution are democratically delegated to a largely automated infrastructure; where people are free to fish in the afternoon and criticize after dinner. It must combine a utopian imagination with the patient organizational work necessary to wrest the future from the clutches of hegemonic neoliberalism.

Strategies and Tactics

In making such claims, Srnicek and Williams are definitely preaching to the leftist choir, rather than trying to convert the masses. However, this choir is not just the audience for, but also the object of, their most vituperative criticism. Indeed, they spend a great deal of the book arguing that the contemporary left has abandoned strategy, universalism, abstraction, and the hard work of building workable, global alternatives to capitalism. Somewhat condescendingly, they group together the highly variegated field of contemporary leftist tactics and organizational forms under the rubric of “folk politics,” which they argue characterizes a commitment to local, horizontal, and immediate actions. The essentially affective, gestural, and experimental politics of movements such as Occupy, for them, are a retreat from the tradition of serious militant politics, to something like “politics-as-drug-experience.”

Whatever their problems with the psychodynamics of such actions, Srnicek and Williams argue convincingly that localism and small-scale, prefigurative politics are simply inadequate to challenging the ideological dominance of neoliberalism — they are out of step with the actualities of the global capitalist system. While they admire the contemporary left’s commitment to self-interrogation, and its micropolitical dedication to the “complete removal of all forms of oppression,” Srnicek and Williams are ultimately neo-Marxists, committed to the view that “[t]he reality of complex, globalised capitalism is that small interventions consisting of relatively non-scalable actions are highly unlikely to ever be able to reorganise our socioeconomic system.” The antidote to this slow localism, however, is decidedly not fast revolution.

Instead, Inventing the Future insists that the left must learn from the strategies that ushered in the currently ascendant neoliberal hegemony. Inventing the Future doesn’t spend a great deal of time luxuriating in pathos, preferring to learn from their enemies’ successes rather than lament their excesses. Indeed, the most empirically interesting chunk of their book is its careful chronicle of the gradual, stepwise movement of neoliberalism from the “fringe theory” of a small group of radicals to the dominant ideological consensus of contemporary capitalism. They trace the roots of the “neoliberal thought collective” to a diverse range of trends in pre–World War II economic thought, which came together in the establishment of a broad publishing and advocacy network in the 1950s, with the explicit strategic aim of winning the hearts and minds of economists, politicians, and journalists. Ultimately, this strategy paid off in the bloodless neoliberal revolutions during the international crises of Keynesianism that emerged in the 1980s.

What made these putsches successful was not just the neoliberal thought collective’s ability to represent political centrism, rational universalism, and scientific abstraction, but also its commitment to organizational hierarchy, internal secrecy, strategic planning, and the establishment of an infrastructure for ideological diffusion. Indeed, the former is in large part an effect of the latter: by the 1980s, neoliberals had already spent decades engaged in the “long-term redefinition of the possible,” ensuring that the institutional and ideological architecture of neoliberalism was already well in place when the economic crises opened the space for swift, expedient action.

Demands

Srnicek and Williams argue that the left must abandon its naïve-Marxist hopes that, somehow, crisis itself will provide the space for direct action to seize the hegemonic position. Instead, it must learn to play the long game as well. It must concentrate on building institutional frameworks and strategic vision, cultivating its own populist universalism to oppose the elite universalism of neoliberal capital. It must also abandon, in so doing, its fear of organizational closure, hierarchy, and rationality, learning instead to embrace them as critical tactical components of universal politics.

There’s nothing particularly new about Srnicek and Williams’s analysis here, however new the problems they identify with the collapse of the left into particularism and localism may be. For the most part, in their vituperations, they are acting as rather straightforward, if somewhat vernacular, followers of the Italian politician and Marxist theorist Antonio Gramsci. As was Gramsci’s, their political vision is one of slow, organizationally sophisticated, passive revolution against the ideological, political, and economic hegemony of capitalism. The gradual war against neoliberalism they envision involves critique and direct action, but will ultimately be won by the establishment of a post-work counterhegemony.

In putting forward their vision of this organization, they strive to articulate demands that would allow for the integration of a wide range of leftist orientations under one populist framework. Most explicitly, they call for the automation of production and the provision of a basic universal income that would provide each person the opportunity to decide how they want to spend their free time: in short, they are calling for the end of work, and for the ideological architecture that supports it. This demand is both utopian and practical; they more or less convincingly argue that a populist, anti-work, pro-automation platform might allow feminist, antiracist, anticapitalist, environmental, anarchist, and postcolonial struggles to become organized together and reinforce one another. Their demands are universal, but designed to reflect a rational universalism that “integrates difference rather than erasing it.” The universal struggle for the future is a struggle for and around “an empty placeholder that is impossible to fill definitively” or finally: the beginning, not the end, of a conversation.

In demanding full automation of production and a universal basic income, Srnicek and Williams are not being millenarian, not calling for a complete rupture with the present, for a complete dismantling and reconfiguration of contemporary political economy. On the contrary, they argue that “it is imperative […] that [the left’s] vision of a new future be grounded upon actually existing tendencies.” Automation and unemployment are the future, regardless of any human intervention; the momentum may be too great to stop the train, but they argue that we can change tracks, can change the meaning of a future without work. In demanding something like fully automated luxury communism, Srnicek and Williams are ultimately asserting the rights of humanity as a whole to share in the spoils of capitalism.

Criticisms

Inventing the Future emerged to a relatively high level of fanfare from leftist social media. Given the publicity, it is unsurprising that other more “engagé” readers have already advanced trenchant and substantive critiques of the future imagined by Srnicek and Williams. More than a few of these critics have pointed out that, despite their repeated insistence that their post-work future is an ecologically sound one, Srnicek and Williams evince roughly zero self-reflection with respect either to the imbrication of microelectronics with brutally extractive regimes of production, or to their own decidedly antiquated, doctrinaire Marxist understanding of humanity’s relationship towards the nonhuman world. Similarly, the question of what the future might mean in the Anthropocene goes largely unexamined.

More damningly, however, others have pointed out that despite the acknowledged counterintuitiveness of their insistence that we must reclaim European universalism against the proliferation of leftist particularisms, their discussions of postcolonial struggle and critique are incredibly shallow. They are keen to insist that their universalism will embrace rather than flatten difference, that it will be somehow less brutal and oppressive than other forms of European univeralism, but do little of the hard argumentative work necessary to support these claims. While we see the start of an answer in their assertion that the rejection of universal access to discourses of science, progress, and rationality might actually function to cement certain subject-positions’ particularity, this — unfortunately — remains only an assertion. At best, they are being uncharitable to potential allies in refusing to take their arguments seriously; at worst, they are unreflexively replicating the form if not the content of patriarchal, racist, and neocolonial capitalist rationality.

For my part, while I find their aggressive and unapologetic presentation of their universalism somewhat off-putting, their project is somewhat harder to criticize than their book — especially as someone acutely aware of the need for more serious forms of organized thinking about the future if we’re trying to push beyond the horizons offered by the neoliberal consensus.

However, as an anthropologist of the computer and data sciences, it’s hard for me to ignore a curious and rather serious lacuna in their thinking about automaticity, algorithms, and computation. Beyond the automation of work itself, they are keen to argue that with contemporary advances in machine intelligence, the time has come to revisit the planned economy. However, in so doing, they curiously seem to ignore how this form of planning threatens to hive off economic activity from political intervention. Instead of fearing a repeat of the privations that poor planning produced in earlier decades, the left should be more concerned with the forms of control and dispossession successful planning produced. The past decade has seen a wealth of social-theoretical research into contemporary forms of algorithmic rationality and control, which has rather convincingly demonstrated the inescapable partiality of such systems and their tendency to be employed as decidedly undemocratic forms of technocratic management.

Srnicek and Williams, however, seem more or less unaware of, or perhaps uninterested in, such research. At the very least, they are extremely overoptimistic about the democratization and diffusion of expertise that would be required for informed mass control over an economy planned by machine intelligence. I agree with their assertion that “any future left must be as technically fluent as it is politically fluent.” However, their definition of technical fluency is exceptionally narrow, confined to an understanding of the affordances and internal dynamics of technical systems rather than a comprehensive analysis of their ramifications within other social structures and processes. I do not mean to suggest that the democratic application of machine learning and complex systems management is somehow a priori impossible, but rather that Srnicek and Williams do not even seem to see how such systems might pose a challenge to human control over the means of production.

In a very real sense, though, my criticisms should be viewed as a part of the very project proposed in the book. Inventing the Future is unapologetically a manifesto, and a much-overdue clarion call to a seriously disorganized metropolitan left to get its shit together, to start thinking — and arguing — seriously about what is to be done. Manifestos, like demands, need to be pointed enough to inspire, while being vague enough to promote dialogue, argument, dissent, and ultimately action. It’s a hard tightrope to walk, and Srnicek and Williams are not always successful. However, Inventing the Future points towards an altogether more coherent and mature project than does their #ACCELERATE MANIFESTO. It is hard to deny the persuasiveness with which the book puts forward the positive contents of a new and vigorous populism; in demanding full automation and universal basic income from the world system, they also demand the return of utopian thinking and serious organization from the left.

Monday, February 22. 2016

Note: can a computer "fake" a human? (hmmm, sounds a bit like Mr. Turing test isn't it?) Or at least be credible enough --because it sounds pretty clear in this video, at that time, that it cannot fake a human and that it is m ore about voice than "intelligence"-- so that the person on the other side of the phone doesn't hang up? This is a funny/uncanny experiment involving D. Sherman at Michigan State University, dating back 1974 and certainly one of the first public trial (or rather social experiment) of a text to speech/voice synthesizer.

Beyond the technical performance, it is the social experiment that is probably even more interesting. It's intertwined and odd nature. You can feel in the voice of the person on the other side of the phone (at the pizza factory --Domino's pizza--) that he really doesn't know how to take it and that the voice sounds like something not heard before. A few trials were necessary before somebody took it "seriously".

Every year, the researchers, students, and technology users who make up the community of the Michigan State University Artificial Language Laboratory celebrate the anniversary of the first use of a speech prosthesis in history: the use by a man with a communication disorder to order a pizza over the telephone using a voice synthesizer. This high-tech sociolinguistic experiment was conducted at the Lab on the evening of December 4, 1974. Donald Sherman, who has Moebius Syndrome and had never ordered a pizza over the phone before, used a system designed by John Eulenberg and J. J. Jackson incorporating a Votrax voice synthesizer, a product of the Federal Screw Works Co. of Troy, Michigan. The inventor of the Votrax voice synthesizer was Richard Gagnon from Birmingham, MI.

The event was covered at the time by the local East Lansing cable news reporter and by a reporter from the State News. About seven years later, in 1981, a BBC production team produced a documentary about the work of the Artificial Language Laboratory and included a scene of a man with cerebral palsy, Michael Williams, ordering a pizza with a newer version of the Lab's speech system. This second pizza order became a part of the documentary, which was broadcast throughout the U.S. as part of the "Nova" science series and internationally as part of the BBC's "Horizon" series.

In January, 1982, the Nova show on the Artificial Language Lab was shown for the first time. The Artificial Language Lab held a premiere party in the Communication Arts and Sciences Building for all the persons who appeared in the program plus all faculty members of the College of Communication Arts and Sciences and their families. The Domino's company generously provided free pizzas for all the guests.

The following December, Domino's again provided pizzas for a party, again held at the Communication Arts building, to commemorate the first ordering of a pizza eight years earlier. The Convocation was held thereafter every year through 1988, each year receiving pizzas through the generous gift of Domino's.

A Communication Enhancement Convocation was held in 1999, celebrating the 25th anniversary of the first pizza order.In addition to Dominos's contribution of pizzas, the Canada Dry Bottling Co. of Lansing provided drinks.The Convocations resumed in 2010 through 2012, when Dr. John Eulenberg advanced to Professor Emeritus status.

At each event, in addition to faculty and students, the convocation guests included local dignitaries from the MSU board of trustees and from the Michigan state legislature. Stevie Wonder, whose first talking computer and first singing computer were designed at the Artificial Language Lab, made telephone appearances and spoke with the youngsters using Artificial Language Lab technology through their
school district special education programs. MSU icons such as the football team, Sparty, and cheer leaders made appearances as well.

Now, through YouTube, we can relive this historical moment and take a thoughtful look back at 40 years of progress in the delivery of augmentative communication technology to persons with disabilities.

Wednesday, April 08. 2015

Songdo in South Korea: a ‘smart city’ whose roads and water, waste and electricity systems are dense with electronic sensors. Photograph: Hotaik Sung/Alamy.

A woman drives to the outskirts of the city and steps directly on to a train; her electric car then drives itself off to park and recharge. A man has a heart attack in the street; the emergency services send a drone equipped with a defibrillator to arrive crucial minutes before an ambulance can. A family of flying maintenance robots lives atop an apartment block – able to autonomously repair cracks or leaks and clear leaves from the gutters.

Such utopian, urban visions help drive the “smart city” rhetoric that has, for the past decade or so, been promulgated most energetically by big technology, engineering and consulting companies. The movement is predicated on ubiquitous wireless broadband and the embedding of computerised sensors into the urban fabric, so that bike racks and lamp posts, CCTV and traffic lights, as well as geeky home appliances such as internet fridges and remote-controlled heating systems, become part of the so-called “internet of things” (the global market for which is now estimated at $1.7tn). Better living through biochemistry gives way to a dream of better living through data. You can even take an MSc in Smart Cities at University College, London.

Yet there are dystopian critiques, too, of what this smart city vision might mean for the ordinary citizen. The phrase itself has sparked a rhetorical battle between techno-utopianists and postmodern flâneurs: should the city be an optimised panopticon, or a melting pot of cultures and ideas?

And what role will the citizen play? That of unpaid data-clerk, voluntarily contributing information to an urban database that is monetised by private companies? Is the city-dweller best visualised as a smoothly moving pixel, travelling to work, shops and home again, on a colourful 3D graphic display? Or is the citizen rightfully an unpredictable source of obstreperous demands and assertions of rights? “Why do smart cities offer only improvement?” asks the architect Rem Koolhaas. “Where is the possibility of transgression?”

The smart city concept arguably dates back at least as far as the invention of automated traffic lights, which were first deployed in 1922 in Houston, Texas. Leo Hollis, author of Cities Are Good For You, says the one unarguably positive achievement of smart city-style thinking in modern times is the train indicator boards on the London Underground. But in the last decade, thanks to the rise of ubiquitous internet connectivity and the miniaturisation of electronics in such now-common devices as RFID tags, the concept seems to have crystallised into an image of the city as a vast, efficient robot – a vision that originated, according to Adam Greenfield at LSE Cities, with giant technology companies such as IBM, Cisco and Software AG, all of whom hoped to profit from big municipal contracts.

“The notion of the smart city in its full contemporary form appears to have originated within these businesses,” Greenfield notes in his 2013 book Against the Smart City, “rather than with any party, group or individual recognised for their contributions to the theory or practice of urban planning.”

Whole new cities, such as Songdo in South Korea, have already been constructed according to this template. Its buildings have automatic climate control and computerised access; its roads and water, waste and electricity systems are dense with electronic sensors to enable the city’s brain to track and respond to the movement of residents. But such places retain an eerie and half-finished feel to visitors – which perhaps shouldn’t be surprising. According to Antony M Townsend, in his 2013 book Smart Cities, Songdo was originally conceived as “a weapon for fighting trade wars”; the idea was “to entice multinationals to set up Asian operations at Songdo … with lower taxes and less regulation”.

In India, meanwhile, prime minister Narendra Modi has promised to build no fewer than 100 smart cities – a competitive response, in part, to China’s inclusion of smart cities as a central tenet of its grand urban plan. Yet for the near-term at least, the sites of true “smart city creativity” arguably remain the planet’s established metropolises such as London, New York, Barcelona and San Francisco. Indeed, many people think London is the smartest city of them all just now — Duncan Wilson of Intel calls it a “living lab” for tech experiments.

So what challenges face technologists hoping to weave cutting-edge networks and gadgets into centuries-old streets and deeply ingrained social habits and patterns of movement? This was the central theme of the recent “Re.Work Future Cities Summit” in London’s Docklands – for which two-day public tickets ran to an eye-watering £600.

The event was structured like a fast-cutting series of TED talks, with 15-minute investor-friendly presentations on everything from “emotional cartography” to biologically inspired buildings. Not one non-Apple-branded laptop could be spotted among the audience, and at least one attendee was seen confidently sporting the telltale fat cyan arm of Google Glass on his head.

“Instead of a smart phone, I want you all to have a smart drone in your pocket,” said one entertaining robotics researcher, before tossing up into the auditorium a camera-equipped drone that buzzed around like a fist-sized mosquito. Speakers enthused about the transport app Citymapper, and how the city of Zurich is both futuristic and remarkably civilised. People spoke about the “huge opportunity” represented by expanding city budgets for technological “solutions”.

Usman Haque’s project Thingful is billed as a ‘search engine for the internet of things’

Strikingly, though, many of the speakers took care to denigrate the idea of the smart city itself, as though it was a once-fashionable buzzphrase that had outlived its usefulness. This was done most entertainingly by Usman Haque, of the urban consultancy Umbrellium. The corporate smart-city rhetoric, he pointed out, was all about efficiency, optimisation, predictability, convenience and security. “You’ll be able to get to work on time; there’ll be a seamless shopping experience, safety through cameras, et cetera. Well, all these things make a city bearable, but they don’t make a city valuable.”

As the tech companies bid for contracts, Haque observed, the real target of their advertising is clear: “The people it really speaks to are the city managers who can say, ‘It wasn’t me who made the decision, it was the data.’”

Of course, these speakers who rejected the corporate, top-down idea of the smart city were themselves demonstrating their own technological initiatives to make the city, well, smarter. Haque’s project Thingful, for example, is billed as a search engine for the internet of things. It could be used in the morning by a cycle commuter: glancing at a personalised dashboard of local data, she could check local pollution levels and traffic, and whether there are bikes in the nearby cycle-hire rack.

“The smart city was the wrong idea pitched in the wrong way to the wrong people,” suggested Dan Hill, of urban innovators the Future Cities Catapult. “It never answered the question: ‘How is it tangibly, materially going to affect the way people live, work, and play?’” (His own work includes Cities Unlocked, an innovative smartphone audio interface that can help visually impaired people navigate the streets.) Hill is involved with Manchester’s current smart city initiative, which includes apparently unglamorous things like overhauling the Oxford Road corridor – a bit of “horrible urban fabric”. This “smart stuff”, Hill tells me, “is no longer just IT – or rather IT is too important to be called IT any more. It’s so important you can’t really ghettoise it in an IT city. A smart city might be a low-carbon city, or a city that’s easy to move around, or a city with jobs and housing. Manchester has recognised that.”

One take-home message of the conference seemed to be that whatever the smart city might be, it will be acceptable as long as it emerges from the ground up: what Hill calls “the bottom-up or citizen-led approach”. But of course, the things that enable that approach – a vast network of sensors amounting to millions of electronic ears, eyes and noses – also potentially enable the future city to be a vast arena of perfect and permanent surveillance by whomever has access to the data feeds.

Inside Rio de Janeiro’s centre of operations: ‘a high-precision control panel for the entire city’. Photograph: David Levene

One only has to look at the hi-tech nerve centre that IBM built for Rio de Janeiro to see this Nineteen Eighty-Four-style vision already alarmingly realised. It is festooned with screens like a Nasa Mission Control for the city. As Townsend writes: “What began as a tool to predict rain and manage flood response morphed into a high-precision control panel for the entire city.” He quotes Rio’s mayor, Eduardo Paes, as boasting: “The operations centre allows us to have people looking into every corner of the city, 24 hours a day, seven days a week.”

What’s more, if an entire city has an “operating system”, what happens when it goes wrong? The one thing that is certain about software is that it crashes. The smart city, according to Hollis, is really just a “perpetual beta city”. We can be sure that accidents will happen – driverless cars will crash; bugs will take down whole transport subsystems or the electricity grid; drones could hit passenger aircraft. How smart will the architects of the smart city look then?

A less intrusive way to make a city smarter might be to give those who govern it a way to try out their decisions in virtual reality before inflicting them on live humans. This is the idea behind city-simulation company Simudyne, whose projects include detailed computerised models for planning earthquake response or hospital evacuation. It’s like the strategy game SimCity – for real cities. And indeed Simudyne now draws a lot of its talent from the world of videogames. “When we started, we were just mathematicians,” explains Justin Lyon, Simudyne’s CEO. “People would look at our simulations and joke that they were inscrutable. So five or six years ago we developed a new system which allows you to make visualisations – pretty pictures.” The simulation can now be run as an immersive first-person gameworld, or as a top-down SimCity-style view, where “you can literally drop policy on to the playing area”.

Another serious use of “pretty pictures” is exemplified by the work of ScanLAB Projects, which uses Lidar and ground-penetrating radar to make 3D visualisations of real places. They can be used for art installations and entertainment: for example, mapping underground ancient Rome for the BBC. But the way an area has been used over time, both above and below ground, can also be presented as a layered historical palimpsest, which can serve the purposes of archaeological justice and memory – as with ScanLAB’s Living Death Camps project with Forensic Architecture, on two concentration-camp sites in the former Yugoslavia.

The former German pavilion at Staro Sajmište, Belgrade – produced from terrestrial laser scanning and ground-penetrating radar as part of the Living Death Camps project. Photograph: ScanLAB Projects

For Simudyne’s simulations, meanwhile, the visualisations work to “gamify” the underlying algorithms and data, so that anyone can play with the initial conditions and watch the consequences unfold. Will there one day be convergence between this kind of thing and the elaborately realistic modelled cities that are built for commercial videogames? “There’s absolutely convergence,” Lyon says. A state-of-the art urban virtual reality such as the recreation of Chicago in this year’s game Watch Dogs requires a budget that runs to scores of millions of dollars. But, Lyon foresees, “Ten years from now, what we see in Watch Dogs today will be very inexpensive.”

What if you could travel through a visually convincing city simulation wearing the VR headset, Oculus Rift? When Lyon first tried one, he says, “Everything changed for me.” Which prompts the uncomfortable thought that when such simulations are indistinguishable from the real thing (apart from the zero possibility of being mugged), some people might prefer to spend their days in them. The smartest city of the future could exist only in our heads, as we spend all our time plugged into a virtual metropolitan reality that is so much better than anything physically built, and fail to notice as the world around us crumbles.

In the meantime, when you hear that cities are being modelled down to individual people – or what in the model are called “agents” – you might still feel a jolt of the uncanny, and insist that free-will makes your actions in the city unpredictable. To which Lyon replies: “They’re absolutely right as individuals, but collectively they’re wrong. While I can’t predict what you are going to do tomorrow, I can have, with some degree of confidence, a sense of what the crowd is going to do, what a group of people is going to do. Plus, if you’re pulling in data all the time, you use that to inform the data of the virtual humans.

“Let’s say there are 30 million people in London: you can have a simulation of all 30 million people that very closely mirrors but is not an exact replica of London. You have the 30 million agents, and then let’s have a business-as-usual normal commute, let’s have a snowstorm, let’s shut down a couple of train lines, or have a terrorist incident, an earthquake, and so on.” Lyons says you will get a highly accurate sense of how people, en masse, will respond to these scenarios. “While I’m not interested in a specific individual, I’m interested in the emergent behaviour of the crowd.”

But what about more nefarious bodies who are interested in specific individuals? As citizens stumble into a future where they will be walking around a city dense with sensors, cameras and drones tracking their every movement – even whether they are smiling (as has already been tested at the Cheltenham Jazz Festival) or feeling gloomy – there is a ticking time-bomb of arguments about surveillance and privacy that will dwarf any previous conversations about Facebook or even, perhaps, government intelligence agencies scanning our email. Unavoidable advertising spam everywhere you go, as in Minority Report, is just the most obvious potential annoyance. (There have already been “smart billboards” that recognised Minis driving past and said hello to them.) The smart city might be a place like Rio on steroids, where you can never disappear.

“If you have a mobile phone, and the right sensors are deployed across the city, people have demonstrated the ability to track those individual phones,” Lyon points out. “And there’s nothing that would prevent you from visualising that movement in a SimCity-like landscape, like in Watch Dogs where you see an avatar moving through the city and you can call up their social-media profile. If you’re trying to search a very large dataset about how someone’s moving, it’s very hard to get your head around it, but as soon as you fire up a game-style visualisation, it’s very easy to see, ‘Oh, that’s where they live, that’s where they work, that’s where their mistress must be, that’s where they go to drink a lot.’”

This is potentially an issue with open-data initiatives such as those currently under way in Bristol and Manchester, which is making publicly available the data it holds about city parking, procurement and planning, public toilets and the fire service. The democratic motivation of this strand of smart-city thinking seems unimpugnable: the creation of municipal datasets is funded by taxes on citizens, so citizens ought to have the right to use them. When presented in the right way – “curated”, if you will, by the city itself, with a sense of local character – such information can help to bring “place back into the digital world”, says Mike Rawlinson of consultancy City ID, which is working with Bristol on such plans.

But how safe is open data? It has already been demonstrated, for instance, that the openly accessible data of London’s cycle-hire scheme can be used to track individual cyclists. “There is the potential to see it all as Big Brother,” Rawlinson says. “If you’re releasing data and people are reusing it, under what purpose and authorship are they doing so?” There needs, Hill says, to be a “reframed social contract”.

The interface of Simudyne’s City Hospital EvacSim

Sometimes, at least, there are good reasons to track particular individuals. Simudyne’s hospital-evacuation model, for example, needs to be tied in to real data. “Those little people that you see [on screen], those are real people, that’s linking to the patient database,” Lyon explains – because, for example, “we need to be able to track this poor child that’s been burned.” But tracking everyone is a different matter: “There could well be a backlash of people wanting literally to go off-grid,” Rawlinson says. Disgruntled smart citizens, unite: you have nothing to lose but your phones.

In truth, competing visions of the smart city are proxies for competing visions of society, and in particular about who holds power in society. “In the end, the smart city will destroy democracy,” Hollis warns. “Like Google, they’ll have enough data not to have to ask you what you want.”

You sometimes see in the smart city’s prophets a kind of casual assumption that politics as we know it is over. One enthusiastic presenter at the Future Cities Summit went so far as to say, with a shrug: “Internet eats everything, and internet will eat government.” In another presentation, about a new kind of “autocatalytic paint” for street furniture that “eats” noxious pollutants such as nitrous oxide, an engineer in a video clip complained: “No one really owns pollution as a problem.” Except that national and local governments do already own pollution as a problem, and have the power to tax and regulate it. Replacing them with smart paint ain’t necessarily the smartest thing to do.

And while some tech-boosters celebrate the power of companies such as Über – the smartphone-based unlicensed-taxi service now banned in Spain and New Delhi, and being sued in several US states – to “disrupt” existing transport infrastructure, Hill asks reasonably: “That Californian ideology that underlies that user experience, should it really be copy-pasted all over the world? Let’s not throw away the idea of universal service that Transport for London adheres to.”

Perhaps the smartest of smart city projects needn’t depend exclusively – or even at all – on sensors and computers. At Future Cities, Julia Alexander of Siemens nominated as one of the “smartest” cities in the world the once-notorious Medellin in Colombia, site of innumerable gang murders a few decades ago. Its problem favelas were reintegrated into the city not with smartphones but with publicly funded sports facilities and a cable car connecting them to the city. “All of a sudden,” Alexander said, “you’ve got communities interacting” in a way they never had before. Last year, Medellin – now the oft-cited poster child for “social urbanism” – was named the most innovative city in the world by the Urban Land Institute.

One sceptical observer of many presentations at the Future Cities Summit, Jonathan Rez of the University of New South Wales, suggests that “a smarter way” to build cities “might be for architects and urban planners to have psychologists and ethnographers on the team.” That would certainly be one way to acquire a better understanding of what technologists call the “end user” – in this case, the citizen. After all, as one of the tribunes asks the crowd in Shakespeare’s Coriolanus: “What is the city but the people?”

fabric | rblg

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